Deep learning is considered the most significant innovation in data science in recent years. At the same time, developers and data scientists are not using deep learning due to relative complexity of customizing deep learning models for their own problems, difficulties in installing and using the required frameworks, and low performance of open source deep learning frameworks on standard CPUs.
This session will show how to easily train and deploy deep learning models for image and text analysis problems, using Intel® Deep Learning SDK, which enables using deep-learning frameworks that were optimized to run fast on regular CPUs and multiple computers, including Caffe and TensorFlow. Intel® Deep Learning SDK includes tools for easy data pre-processing and for model compression, providing an end-to-end solution to the problem. In addition it supports scale-out on multiple computers for training, as well as using compression methods and optimization for deployment of the models on various intel HW platforms, including with limited memory footprints and performance constrains.